Modelling users' contextual querying behaviour for web image searching

The rapid growth of visual information on Web has led to immense interest in multimedia information retrieval (MIR). While advancement in MIR systems has achieved some success in specific domains, particularly the content-based approaches, general Web users still struggle to find the images they want. Despite the success in content-based object recognition or concept extraction, the major problem in current Web image searching remains in the querying process. Since most online users only express their needs in semantic terms or objects, systems that utilize visual features (e.g., color or texture) to search images create a semantic gap which hinders general users from fully expressing their needs. In addition, query-by-example (QBE) retrieval imposes extra obstacles for exploratory search because users may not always have the representative image at hand or in mind when starting a search (i.e. the page zero problem). As a result, the majority of current online image search engines (e.g., Google, Yahoo, and Flickr) still primarily use textual queries to search. The problem with query-based retrieval systems is that they only capture users’ information need in terms of formal queries;; the implicit and abstract parts of users’ information needs are inevitably overlooked. Hence, users often struggle to formulate queries that best represent their needs, and some compromises have to be made. Studies of Web search logs suggest that multimedia searches are more difficult than textual Web searches, and Web image searching is the most difficult compared to video or audio searches. Hence, online users need to put in more effort when searching multimedia contents, especially for image searches. Most interactions in Web image searching occur during query reformulation. While log analysis provides intriguing views on how the majority of users search, their search needs or motivations are ultimately neglected. User studies on image searching have attempted to understand users’ search contexts in terms of users’ background (e.g., knowledge, profession, motivation for search and task types) and the search outcomes (e.g., use of retrieved images, search performance). However, these studies typically focused on particular domains with a selective group of professional users. General users’ Web image searching contexts and behaviors are little understood although they represent the majority of online image searching activities nowadays. We argue that only by understanding Web image users’ contexts can the current Web search engines further improve their usefulness and provide more efficient searches. In order to understand users’ search contexts, a user study was conducted based on university students’ Web image searching in News, Travel, and commercial Product domains. The three search domains were deliberately chosen to reflect image users’ interests in people, time, event, location, and objects. We investigated participants’ Web image searching behavior, with the focus on query reformulation and search strategies. Participants’ search contexts such as their search background, motivation for search, and search outcomes were gathered by questionnaires. The searching activity was recorded with participants’ think aloud data for analyzing significant search patterns. The relationships between participants’ search contexts and corresponding search strategies were discovered by Grounded Theory approach. Our key findings include the following aspects: - Effects of users' interactive intents on query reformulation patterns and search strategies - Effects of task domain on task specificity and task difficulty, as well as on some specific searching behaviors - Effects of searching experience on result expansion strategies A contextual image searching model was constructed based on these findings. The model helped us understand Web image searching from user perspective, and introduced a context-aware searching paradigm for current retrieval systems. A query recommendation tool was also developed to demonstrate how users’ query reformulation contexts can potentially contribute to more efficient searching.

Automatic query expansion : a structural linguistic perspective

A user’s query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques ignore information about the dependencies that exist between words in natural language. However, more recent approaches have demonstrated that by explicitly modeling associations between terms significant improvements in retrieval effectiveness can be achieved over those that ignore these dependencies. State-of-the-art dependency-based approaches have been shown to primarily model syntagmatic associations. Syntagmatic associations infer a likelihood that two terms co-occur more often than by chance. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process will improve retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine.

Term associations in query expansion : a structural linguistic perspective

Many successful query expansion techniques ignore information about the term dependencies that exist within natural language. However, researchers have recently demonstrated that consistent and significant improvements in retrieval effectiveness can be achieved by explicitly modelling term dependencies within the query expansion process. This has created an increased interest in dependency-based models. State-of-the-art dependency-based approaches primarily model term associations known within structural linguistics as syntagmatic associations, which are formed when terms co-occur together more often than by chance. However, structural linguistics proposes that the meaning of a word is also dependent on its paradigmatic associations, which are formed between words that can substitute for each other without effecting the acceptability of a sentence. Given the reliance on word meanings when a user formulates their query, our approach takes the novel step of modelling both syntagmatic and paradigmatic associations within the query expansion process based on the (pseudo) relevant documents returned in web search. The results demonstrate that this approach can provide significant improvements in web re- trieval effectiveness when compared to a strong benchmark retrieval system.

Secured e-health data retrieval in DaaS and Big Data

Big Data is a rising IT trend similar to cloud computing, social networking or ubiquitous computing. Big Data can offer beneficial scenarios in the e-health arena. However, one of the scenarios can be that Big Data needs to be kept secured for a long period of time in order to gain its benefits such as finding cures for infectious diseases and protecting patient privacy. From this connection, it is beneficial to analyse Big Data to make meaningful information while the data is stored securely. Therefore, the analysis of various database encryption techniques is essential. In this study, we simulated 3 types of technical environments, namely, Plain-text, Microsoft Built-in Encryption, and custom Advanced Encryption Standard, using Bucket Index in Data-as-a-Service. The results showed that custom AES-DaaS has a faster range query response time than MS built-in encryption. Furthermore, while carrying out the scalability test, we acknowledged that there are performance thresholds depending on physical IT resources. Therefore, for the purpose of efficient Big Data management in eHealth it is noteworthy to examine their scalability limits as well even if it is under a cloud computing environment. In addition, when designing an e-health database, both patient privacy and system performance needs to be dealt as top priorities.

Diurnal variation of small and large ion concentrations in an urban location

A Neutral cluster and Air Ion Spectrometer (NAIS) was used to monitor the concentration of airborne ions on 258 full days between Nov 2011 and Dec 2012 in Brisbane, Australia. The air was sampled from outside a window on the sixth floor of a building close to the city centre, approximately 100 m away from a busy freeway. The NAIS detects all ions and charged particles smaller than 42 nm. It was operated in a 4 min measurement cycle, with ion data recorded at 10 s intervals over 2 min during each cycle. The data were analysed to derive the diurnal variation of small, large and total ion concentrations in the environment. We adapt the definition of Horrak et al (2000) and classify small ions as molecular clusters smaller than 1.6 nm and large ions as charged particles larger than this size...

Representing and discovering adversarial team behaviors using player roles

In this paper, we describe a method to represent and discover adversarial group behavior in a continuous domain. In comparison to other types of behavior, adversarial behavior is heavily structured as the location of a player (or agent) is dependent both on their teammates and adversaries, in addition to the tactics or strategies of the team. We present a method which can exploit this relationship through the use of a spatiotemporal basis model. As players constantly change roles during a match, we show that employing a "role-based" representation instead of one based on player "identity" can best exploit the playing structure. As vision-based systems currently do not provide perfect detection/tracking (e.g. missed or false detections), we show that our compact representation can effectively "denoise" erroneous detections as well as enabe temporal analysis, which was previously prohibitive due to the dimensionality of the signal. To evaluate our approach, we used a fully instrumented field-hockey pitch with 8 fixed high-definition (HD) cameras and evaluated our approach on approximately 200,000 frames of data from a state-of-the-art real-time player detector and compare it to manually labelled data.

Sequential decision fusion of multibiometrics applied to text-dependent speaker verification for controlled errors

Reliability of the performance of biometric identity verification systems remains a significant challenge. Individual biometric samples of the same person (identity class) are not identical at each presentation and performance degradation arises from intra-class variability and inter-class similarity. These limitations lead to false accepts and false rejects that are dependent. It is therefore difficult to reduce the rate of one type of error without increasing the other. The focus of this dissertation is to investigate a method based on classifier fusion techniques to better control the trade-off between the verification errors using text-dependent speaker verification as the test platform. A sequential classifier fusion architecture that integrates multi-instance and multisample fusion schemes is proposed. This fusion method enables a controlled trade-off between false alarms and false rejects. For statistically independent classifier decisions, analytical expressions for each type of verification error are derived using base classifier performances. As this assumption may not be always valid, these expressions are modified to incorporate the correlation between statistically dependent decisions from clients and impostors. The architecture is empirically evaluated by applying the proposed architecture for text dependent speaker verification using the Hidden Markov Model based digit dependent speaker models in each stage with multiple attempts for each digit utterance. The trade-off between the verification errors is controlled using the parameters, number of decision stages (instances) and the number of attempts at each decision stage (samples), fine-tuned on evaluation/tune set. The statistical validation of the derived expressions for error estimates is evaluated on test data. The performance of the sequential method is further demonstrated to depend on the order of the combination of digits (instances) and the nature of repetitive attempts (samples). The false rejection and false acceptance rates for proposed fusion are estimated using the base classifier performances, the variance in correlation between classifier decisions and the sequence of classifiers with favourable dependence selected using the 'Sequential Error Ratio' criteria. The error rates are better estimated by incorporating user-dependent (such as speaker-dependent thresholds and speaker-specific digit combinations) and class-dependent (such as clientimpostor dependent favourable combinations and class-error based threshold estimation) information. The proposed architecture is desirable in most of the speaker verification applications such as remote authentication, telephone and internet shopping applications. The tuning of parameters - the number of instances and samples - serve both the security and user convenience requirements of speaker-specific verification. The architecture investigated here is applicable to verification using other biometric modalities such as handwriting, fingerprints and key strokes.

A novel representation of bioacoustic events for content-based search in field audio data

Bioacoustic data can provide an important base for environmental monitoring. To explore a large amount of field recordings collected, an automated similarity search algorithm is presented in this paper. A region of an audio defined by frequency and time bounds is provided by a user; the content of the region is used to construct a query. In the retrieving process, our algorithm will automatically scan through recordings to search for similar regions. In detail, we present a feature extraction approach based on the visual content of vocalisations – in this case ridges, and develop a generic regional representation of vocalisations for indexing. Our feature extraction method works best for bird vocalisations showing ridge characteristics. The regional representation method allows the content of an arbitrary region of a continuous recording to be described in a compressed format.

Reliability and validity of query intent assessments

In most intent recognition studies, annotations of query intent are created post hoc by external assessors who are not the searchers themselves. It is important for the field to get a better understanding of the quality of this process as an approximation for determining the searcher's actual intent. Some studies have investigated the reliability of the query intent annotation process by measuring the interassessor agreement. However, these studies did not measure the validity of the judgments, that is, to what extent the annotations match the searcher's actual intent. In this study, we asked both the searchers themselves and external assessors to classify queries using the same intent classification scheme. We show that of the seven dimensions in our intent classification scheme, four can reliably be used for query annotation. Of these four, only the annotations on the topic and spatial sensitivity dimension are valid when compared with the searcher's annotations. The difference between the interassessor agreement and the assessor-searcher agreement was significant on all dimensions, showing that the agreement between external assessors is not a good estimator of the validity of the intent classifications. Therefore, we encourage the research community to consider using query intent classifications by the searchers themselves as test data.

Metastability and emergent performance of dynamic interceptive actions

Objectives: Adaptive patterning of human movement is context specific and dependent on interacting constraints of the performer–environment relationship. Flexibility of skilled behaviour is predicated on the capacity of performers to move between different states of movement organisation to satisfy dynamic task constraints, previously demonstrated in studies of visual perception, bimanual coordination, and an interceptive combat task. Metastability is a movement system property that helps performers to remain in a state of relative coordination with their performance environments, poised between multiple co-existing states (stable and distinct movement patterns or responses). The aim of this study was to examine whether metastability could be exploited in externally paced interceptive actions in fast ball sports, such as cricket. Design: Here we report data on metastability in performance of multi-articular hitting actions by skilled junior cricket batters (n = 5). Methods: Participants’ batting actions (key movement timings and performance outcomes) were analysed in four distinct performance regions varied by ball pitching (bounce) location. Results: Results demonstrated that, at a pre-determined distance to the ball, participants were forced into a meta-stable region of performance where rich and varied patterns of functional movement behaviours emerged. Participants adapted the organisation of responses, resulting in higher levels of variability in movement timing in this performance region, without detrimental effects on the quality of interceptive performance outcomes. Conclusions: Findings provide evidence for the emergence of metastability in a dynamic interceptive action in cricket batting. Flexibility and diversity of movement responses were optimised using experiential knowledge and careful manipulation of key task constraints of the specific sport context.

Low formalin concentrations induce fine-tuned responses that are sex and age-dependent : a developmental study

The formalin test is increasingly applied as a model of inflammatory pain using high formalin concentrations (5–15%). However, little is known about the effects of low formalin concentrations on related behavioural responses. To examine this, rat pups were subjected to various concentrations of formalin at four developmental stages: 7, 13, 22, and 82 days of age. At postnatal day (PND) 7, sex differences in flinching but not licking responses were observed with 0.5% formalin evoking higher flinching in males than in females. A dose response was evident in that 0.5% formalin also produced higher licking responses compared to 0.3% or 0.4% formalin. At PND 13, a concentration of 0.8% formalin evoked a biphasic response. At PND 22, a concentration of 1.1% evoked higher flinching and licking responses during the late phase (10–30 min) in both males and females. During the early phase (0–5 min), 1.1% evoked higher licking responses compared to 0.9% or 1% formalin. 1.1% formalin produced a biphasic response that was not evident with 0.9 or 1%. At PND 82, rats displayed a biphasic pattern in response to three formalin concentrations (1.25%, 1.75% and 2.25%) with the presence of an interphase for both 1.75% and 2.25% but not for 1.25%. These data suggest that low formalin concentrations induce fine-tuned responses that are not apparent with the high formalin concentration commonly used in the formalin test. These data also show that the developing nociceptive system is very sensitive to subtle changes in formalin concentrations.

Osteocyte-induced angiogenesis via VEGF–MAPK-dependent pathways in endothelial cells

Recently, it has been suggested osteocytes control the activities of bone formation (osteoblasts) and resorption (osteoclast), indicating their important regulatory role in bone remodelling. However, to date, the role of osteocytes in controlling bone vascularisation remains unknown. Our aim was to investigate the interaction between endothelial cells and osteocytes and to explore the possible molecular mechanisms during angiogenesis. To model osteocyte/endothelial cell interactions, we co-cultured osteocyte cell line (MLOY4) with endothelial cell line (HUVECs). Co-cultures were performed in 1:1 mixture of osteocytes and endothelial cells or by using the conditioned media (CM) transfer method. Real-time cell migration of HUVECs was measured with the transwell migration assay and xCELLigence system. Expression levels of angiogenesis- related genes were measured by quantitative real-time polymerase chain reaction (qRT-PCR). The effect of vascular endothelial growth factor (VEGF) and mitogen-activated phosphorylated kinase (MAPK) signaling were monitored by western blotting using relevant antibodies and inhibitors. During the bone formation, it was noted that osteocyte dendritic processes were closely connected to the blood vessels. The CM generated from MLOY4 cells-activated proliferation, migration, tube-like structure formation, and upregulation of angiogenic genes in endothelial cells suggesting that secretory factor(s) from osteocytes could be responsible for angiogenesis. Furthermore, we identified that VEGF secreted from MLOY4-activated VEGFR2–MAPK–ERK-signaling pathways in HUVECs. Inhibiting VEGF and/or MAPK–ERK pathways abrogated osteocyte-mediated angiogenesis in HUVEC cells. Our data suggest an important role of osteocytes in regulating angiogenesis.

Time course-dependent changes in the transcriptome of human skeletal muscle during recovery from endurance exercise: From inflammation to adaptive remodeling

Re-programming of gene expression is fundamental for skeletal muscle adaptations in response to endurance exercise. This study investigated the time-course dependent changes in the muscular transcriptome following an endurance exercise trial consisting of 1 h of intense cycling immediately followed by 1 h of intense running. Skeletal muscle samples were taken at baseline, 3 h, 48 h, and 96 h post-exercise from eight healthy, endurance-trained, male individuals. RNA was extracted from muscle. Differential gene expression was evaluated using Illumina microarrays and validated with qPCR. Gene set enrichment analysis identified enriched molecular signatures chosen from the Molecular Signatures Database. Three h post-exercise, 102 gene sets were up-regulated [family wise error rate (FWER), P < 0.05]; including groups of genes related with leukocyte migration, immune and chaperone activation, and cyclic AMP responsive element binding protein (CREB) 1-signaling. Forty-eight h post-exercise, among 19 enriched gene sets (FWER, P < 0.05), two gene sets related to actin cytoskeleton remodeling were up-regulated. Ninety-six h post-exercise, 83 gene sets were enriched (FWER, P < 0.05), 80 of which were up-regulated; including gene groups related to chemokine signaling, cell stress management, and extracellular matrix remodeling. These data provide comprehensive insights into the molecular pathways involved in acute stress, recovery, and adaptive muscular responses to endurance exercise. The novel 96 h post-exercise transcriptome indicates substantial transcriptional activity, potentially associated with the prolonged presence of leukocytes in the muscles. This suggests that muscular recovery, from a transcriptional perspective, is incomplete 96 h after endurance exercise involving muscle damage.

Shrinkage empirical likelihood estimator in longitudinal analysis with time-dependent covariates-application to modeling the health of Filipino children

The method of generalized estimating equations (GEE) is a popular tool for analysing longitudinal (panel) data. Often, the covariates collected are time-dependent in nature, for example, age, relapse status, monthly income. When using GEE to analyse longitudinal data with time-dependent covariates, crucial assumptions about the covariates are necessary for valid inferences to be drawn. When those assumptions do not hold or cannot be verified, Pepe and Anderson (1994, Communications in Statistics, Simulations and Computation 23, 939–951) advocated using an independence working correlation assumption in the GEE model as a robust approach. However, using GEE with the independence correlation assumption may lead to significant efficiency loss (Fitzmaurice, 1995, Biometrics 51, 309–317). In this article, we propose a method that extracts additional information from the estimating equations that are excluded by the independence assumption. The method always includes the estimating equations under the independence assumption and the contribution from the remaining estimating equations is weighted according to the likelihood of each equation being a consistent estimating equation and the information it carries. We apply the method to a longitudinal study of the health of a group of Filipino children.

Data requirements of hedonic models in determining the impact of infrastructure charges on new housing costs

The use of hedonic models to estimate the effects of various factors on house prices is well established. This paper examines a number of international hedonic house price models that seek to quantify the effect of infrastructure charges on new house prices. This work is an important factor in the housing affordability debate, with many governments in high growth areas having user-pays infrastructure charging policies operating in tandem with housing affordability objectives, with no empirical evidence on the impact of one on the other. This research finds there is little consistency between existing models and the data sets utilised. Specification appears dependent upon data availability rather than sound theoretical grounding. This may lead to a lack of external validity with model specification dependent upon data availability rather than sound theoretical grounding.